[논문]다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가

서영민; 권구호; 최윤영; 이병준

doi:10.15681/kswe.2021.37.6.520

Abstract ▼ AI-Helper

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (...

Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

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표/그림 (14)

그림 Fig. 1. Study area and water quality monitoring stations.
그림 Fig. 2. GIS data for developing HSPF model.
그림 Fig. 3. HSPF network model.
그림 Fig. 4. Correlation matrix plots for water quality time series (temp: water temperature, EC: electrical conductivity, and Q: river discharge).
표 Table 1. Contribution and correlation of variables for the first and second principal components (Geumho A)
표 Table 2. Contribution and correlation of variables for the first and second principal components (Geumho B)
그림 Fig. 5. Correlation circles for water quality time series.
그림 Fig. 6. Biplots for water quality times series.
표 Table 3. Cluster composition for water quality variables and season
그림 Fig. 7. Correlation matrix plot for spatial water quality data.
표 Table 4. Contribution and correlation of variables for the first and second principal components (spatial water quality data)
그림 Fig. 8. Cluster analysis for spatial water quality variables.
그림 Fig. 9. Comparison of observed and predicted values.
그림 Fig. 10. Temporal and spatial patterns of BOD, T-N and T-P.

참고문헌 (13)

Cho, Y. C., Lee, S. W., Ryu, I. G., and Yu, S. J. (2017). Assessment of spatiotemporal water quality variation using multivariate statistical techniques: A case study of the Imjin river basin, Korea, Journal of Korean Society of Environmental Engineers, 39(11), 641-649.
Jung, S. J., Kim, K. S., Seo, D. J., Kim, J. H., and Lim, B. J. (2013). Evaluation of water quality characteristics and grade classification of Yeongsan river tributaries, Journal of Korean Society on Water Environment, 29(4), 504-513.
Jung, K. Y., Ahn, J. M., Kim, K., Lee, I. J., and Yang, D. S. (2016). Evaluation of water quality characteristics and water quality improvement grade classification of Geumho river tributaries, Journal of Environmental Science International, 25(6), 767-787.
Kim, S. R. and Kim, S. M. (2020). Analysis of livestock nonpoint source pollutant load ratio for each sub-watershed in Sancheong Watershed using HSPF model, Journal of the Korean Society of Agricultural Engineers, 62(1), 39-50.
Kim, Y., Gal, B., Park, J., Kim, S., and Im, T. (2018). Classification of Nakdong river tributaries under priority management based on their characteristics and water quality index, Journal of Korean Society of Environmental Engineers, 40(2), 73-81.

상세보기
Lee, J. W., Kwon, H. G., Yi, Y. J., Yoon, J. S., Han, K. Y., and Cheon, S. U. (2012). Quantitative estimation of nonpoint source load by BASINS/HSPF, Journal of Environmental Science International, 21(8), 965-975.
Lee, S., Kim, J. M., Shin, H. S., and Kwon, S. (2019). Evaluation of riparian buffer for the reduction efficiency of non-point sources using HSPF model, Journal of the Korean Science of Hazard Mitigation, 19(1), 341-349.
Park, J. H., Moon, M. J., and Kim, K. S. (2014). Analysis of relationship between water quality parameters with land use in Yeongsan river basin, Journal of Environmental Impact Assessment, 23(1), 19-27.
Seo, M., Cho, C., Im, T., Kim, S., Yoon, H., Kim, Y., and Kim, G. (2019). Statistical analysis of the spatio-temporal water quality characteristics of the Nakdong river, Journal of Environmental Science International, 28(3), 303-320.
Shrestaha, S. and Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan, Environmental Modelling and Software, 22, 464-475.

상세보기
United States Environmental Protection Agency (U.S. EPA) (2001). WinHSPF Version 2.0 User's Manual, Contract No. 68-C-98-010, U.S. EPA, Washington, DC.
Kim, J. H. (2015). R Multivariate statistical analysis, Kyowoosa, Seoul.
Daegu Regional Environmental Office (DREO) (2021). Investigation on pollutant source loading and development of a hydrological model in the Geumho river basin, Daegu Regional Environmental Office, Ministry of Environment.

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다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가
Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed Environmental Model 원문보기

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다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가 Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed Environmental Model 원문보기

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다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가
Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed Environmental Model 원문보기

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